TY - JOUR
AB - We consider a two-dimensional magnetic Schrödinger operator on a square lattice with a spatially stationary random magnetic field. We prove Anderson localization near the spectral edges. We use a new approach to establish a Wegner estimate that does not rely on the monotonicity of the energy on the random parameters.
AU - László Erdös
AU - Hasler, David G
ID - 2779
IS - 8
JF - Annales Henri Poincare
TI - Wegner estimate for random magnetic Laplacian on ℤ 2
VL - 13
ER -
TY - JOUR
AB - When a binary fluid demixes under a slow temperature ramp, nucleation, coarsening and sedimentation of droplets lead to an oscillatory evolution of the phase-separating system. The advection of the sedimenting droplets is found to be chaotic. The flow is driven by density differences between two phases. Here, we show how image processing can be combined with particle tracking to resolve droplet size and velocity simultaneously. Droplets are used as tracer particles, and the sedimentation velocity is determined. Taking these effects into account, droplets with radii in the range of 4-40 μm are detected and tracked. Based on these data, we resolve the oscillations in the droplet size distribution that are coupled to the convective flow.
AU - Lapp, Tobias
AU - Rohloff, Martin
AU - Vollmer, Jürgen T
AU - Björn Hof
ID - 2802
IS - 5
JF - Experiments in Fluids
TI - Particle tracking for polydisperse sedimenting droplets in phase separation
VL - 52
ER -
TY - JOUR
AB - Recent numerical studies suggest that in pipe and related shear flows, the region of phase space separating laminar from turbulent motion is organized by a chaotic attractor, called an edge state, which mediates the transition process. We here confirm the existence of the edge state in laboratory experiments. We observe that it governs the dynamics during the decay of turbulence underlining its potential relevance for turbulence control. In addition we unveil two unstable traveling wave solutions underlying the experimental flow fields. This observation corroborates earlier suggestions that unstable solutions organize turbulence and its stability border.
AU - de Lózar, Alberto
AU - Mellibovsky, Fernando
AU - Avila, Marc
AU - Björn Hof
ID - 2803
IS - 21
JF - Physical Review Letters
TI - Edge state in pipe flow experiments
VL - 108
ER -
TY - JOUR
AB - The analysis of the size distribution of droplets condensing on a substrate (breath figures) is a test ground for scaling theories. Here, we show that a faithful description of these distributions must explicitly deal with the growth mechanisms of the droplets. This finding establishes a gateway connecting nucleation and growth of the smallest droplets on surfaces to gross features of the evolution of the droplet size distribution
AU - Blaschke, Johannes
AU - Lapp, Tobias
AU - Björn Hof
AU - Vollmer, Jürgen T
ID - 2804
IS - 6
JF - Physical Review Letters
TI - Breath figures: Nucleation, growth, coalescence, and the size distribution of droplets
VL - 109
ER -
TY - CONF
AB - We study the problem of maximum marginal prediction (MMP) in probabilistic graphical models, a task that occurs, for example, as the Bayes optimal decision rule under a Hamming loss. MMP is typically performed as a two-stage procedure: one estimates each variable's marginal probability and then forms a prediction from the states of maximal probability. In this work we propose a simple yet effective technique for accelerating MMP when inference is sampling-based: instead of the above two-stage procedure we directly estimate the posterior probability of each decision variable. This allows us to identify the point of time when we are sufficiently certain about any individual decision. Whenever this is the case, we dynamically prune the variables we are confident about from the underlying factor graph. Consequently, at any time only samples of variables whose decision is still uncertain need to be created. Experiments in two prototypical scenarios, multi-label classification and image inpainting, show that adaptive sampling can drastically accelerate MMP without sacrificing prediction accuracy.
AU - Lampert, Christoph
ID - 2825
TI - Dynamic pruning of factor graphs for maximum marginal prediction
VL - 1
ER -